计算机工程2011，Vol.37Issue(5)：74-76,3.
自适应概念漂移的在线集成分类器
Online Ensemble Classifier for Adaptive Concept Drift
王黎明 1周驰1
作者信息
- 1. 郑州大学信息工程学院,郑州,450001
- 折叠
摘要
Abstract
Mining data streams require algorithms that make fast response, make light demands on memory resources and are easily to adapt to concept drift.This paper proposes a new algorithm for data streaming mining with concept drift called AHBag, which is based on Hoeffding tree online Bagging ensemble.The algorithm tests data within an adaptive window using the statistical theory for capturing the concept drift.According to the test results to update Hoeffding tree or rebuild a new Hoeffding trees.Experimental results show that the algorithm has a highly accuracy in dealing with data streams with concept drift.关键词
数据流/概念漂移/Hoeffding树/在线BaggingKey words
data stream/ concept drift/ Hoeffding tree/ online Bagging分类
信息技术与安全科学引用本文复制引用
王黎明,周驰..自适应概念漂移的在线集成分类器[J].计算机工程,2011,37(5):74-76,3.
